Distributed Databases Questions Long
Distributed concurrency control refers to the management of concurrent access to data in a distributed database system. It ensures that multiple transactions executing concurrently in different nodes of the distributed system do not interfere with each other and maintain the consistency and integrity of the database.
There are several techniques used to manage distributed concurrency control:
1. Locking: Locking is a widely used technique in distributed concurrency control. It involves acquiring locks on data items to prevent other transactions from accessing or modifying them. Locks can be of different types such as shared locks (read-only access) and exclusive locks (write access). Distributed locking protocols like Two-Phase Locking (2PL) and Strict Two-Phase Locking (S2PL) are used to coordinate the acquisition and release of locks across multiple nodes.
2. Timestamp ordering: In this technique, each transaction is assigned a unique timestamp based on its start time. Transactions are then ordered based on their timestamps, and conflicts between transactions are resolved by comparing their timestamps. The transaction with the earlier timestamp is allowed to proceed, while the other transaction is rolled back and restarted later.
3. Optimistic concurrency control: This approach assumes that conflicts between transactions are rare, and most transactions can execute concurrently without interference. Transactions are allowed to proceed without acquiring locks, and conflicts are detected during the commit phase. If conflicts are detected, one or more transactions may need to be rolled back and restarted.
4. Multi-version concurrency control (MVCC): MVCC maintains multiple versions of data items to allow concurrent access. Each transaction sees a consistent snapshot of the database at the time it started. When a transaction modifies a data item, a new version is created, and other transactions continue to access the old version. This allows for high concurrency as transactions can read and write data simultaneously.
5. Distributed deadlock detection: Deadlocks can occur in distributed systems when multiple transactions are waiting for resources held by each other, resulting in a circular dependency. Distributed deadlock detection algorithms like the Wait-for Graph (WFG) algorithm are used to detect and resolve deadlocks by identifying the circular dependencies and aborting one or more transactions involved.
Overall, managing distributed concurrency control involves a combination of these techniques to ensure that transactions can execute concurrently while maintaining data consistency and integrity in a distributed database system.